1. Field of the Invention
This invention generally relates to estimating the position of the mobile device in a wireless communication network and, more specifically, to determining the distance of the mobile device from fixed-position wireless communication stations and using those distances to estimate the position of the mobile device.
2. Description of Related Art
In recent years the number of mobile computing and communication devices has increased dramatically, creating the need for more advanced mobile and wireless services. Mobile email, walkie-talkie services, multi-player gaming and call-following are examples of new applications for mobile devices. Because mobile devices are not tethered to any fixed location, users are also beginning to demand applications that are able to discover and use their current location. On the regulatory front, the FCC enhanced 911 rules mandate that mobile telephones must be able to supply location information to emergency operators when making 911 calls (www.fcc.gov/pshs/services/911-services/enhanced911/). In each case, it is essential that the mobile device be able to estimate its location and return that information to the user or other entities.
Location-based services (LBS) are an emerging area of mobile applications that leverage mobile location systems. Examples of these services range from obtaining local weather, traffic updates, and driving directions to child trackers, buddy finders and urban concierge services. The new location-aware devices that facilitate LBS rely on a variety of positioning technologies that all use the same basic concept. By measuring radio signals originating from or arriving at known reference points, these technologies can estimate the mobile device's position relative to the reference points. In cellular positioning systems (CPS) the reference points are the cellular installations (referred to in this work as cells or cell towers), and the observed signals are transmissions defined by cellular communication standards including but not limited to GSM, cdmaOne, UMTS, cdma2000, WiMax, and LTE.
As used herein, cellular positioning systems are limited to technologies that use only cellular installations and signals for location estimation. Thus, systems such as the satellite-based global positioning system (GPS) (www8.garmin.com/aboutGPS/), hybrid satellite-cellular assisted-GPS (A-GPS) (http://www.gpsworld.com/gpsworld/article/articleDetail.jsp?id=12287), wi-fi positioning (WPS) based on IEEE 802.11 access points (www.skyhookwireless.com/howitworks/wps.php), or hybrid wifi-GPS positioning (www.skyhookwireless.com/howitworks/) are not considered a cellular positioning system. In addition, pattern matching or so-called “fingerprinting” CPS technologies as developed by Placelab and others (“Practical Metropolitan-Scale Positioning for GSM Phones”, Chen et al, available at www.placelab.org/publications/pubs/gsm-ubicomp2006.pdf) are excluded from the meaning of cellular positioning systems because those approaches have no concept of reference point location or range estimation.
There are many fundamentally different approaches to designing cellular positioning systems, but they can be organized in terms of the observable signal parameters that are used for location estimation. Time-based systems use measurements of the time between transmission and reception of a signal to estimate the distance between the transmitter and the receiver. Such systems employ time of arrival (TOA) or time-difference of arrival (TDOA) schemes to generate range estimates for use in a variety of algorithms to generate position estimates for the user (US RE38,808, Schuchman, et al; US 2002/007715 A1, Ruutu, et al; www.trueposition.com/web/guest/white-papers#). Time-based systems often require tight synchronization between the different cellular installations because the error in the range estimates is directly related to the synchronization error between the cells. In systems such as cdmaOne where synchronization is intrinsic to the standard, it is relatively straightforward to implement time-based range estimation. However, in asynchronous systems such as GSM and UMTS, additional equipment is often installed at each cell at significant additional cost (U.S. Pat. No. 6,275,705 B1, Drane, et al; U.S. Pat. No. 6,526,039 B1, Dahlman, et al.; U.S. Pat. No. 6,901,264 B2, Myr; www.trueposition.com/web/guest/trueposition-location-platform).
As part of the WCDMA standard, time-based range estimation can be calculated according to the round trip time (RTT) of a packet sent from the cell to the mobile and returned immediately from the mobile to the cell (www.trueposition.com/web/guest/e-cid;). This approach does not require synchronization, but it only works with network-based positioning systems. That is, the network can learn the position of the mobile, but the mobile does not know its own position unless it receives a specific message carrying the network's position estimate. Regardless of the specific range-estimation technique, time-based systems are extremely susceptible to errors caused by multipath propagation. Essentially, late-arriving reflections of the signal cause the system to overestimate the mobile to cell range.
As an alternative to time-based range estimation, many systems use received signal strength (RSS) to estimate the distance from the mobile to the transmitting cell (“Indoor/Outdoor Location of Cellular Handsets Based on Received Signal Strength” by Zhu and Durgin, available at www.propagation.gatech.edu/radiolocation/PolarisReport.pdf). Well-known pathloss models show that signal power falls exponentially with distance, so knowledge of the pathloss exponent and other parameters such as antenna gain and transmit power allows the positioning system to compute range estimates. However, signal power can vary dramatically in unpredictable ways due to fading and other environmental factors. Thus, the uncertainty inherent to RSS measurements limits the accuracy of RSS-based range estimates. Alternatively, the RSS can be used directly in centroid-based schemes in which there is no explicit range estimation. Nearest neighbor-type location estimation (also known as Cell ID) in which the mobile's position is estimated using only the most powerful observed cell is a degenerate case of RSS-based positioning.